googleway

library(googleway)
set_key(read.dcf("~/Documents/.googleAPI", fields = "GOOGLE_MAP_KEY"), api = "map")
set_key(read.dcf("~/Documents/.googleAPI", fields = "GOOGLE_API_KEY"))

The googleway library provides access to Google Maps API, both for creating maps, and using the mapping services such as geocoding and searching for places.

To use any of Google Map’s services you will need an API key.

Most mapping libraries in R support plotting shapes and layers. An advantage with googleway is access to their own traffic, bicycliing, transit and streetview layers. For example, to overlay traffic information call add_traffic().

google_map(location = c(-37.81, 144.97), zoom = 12) %>%
  add_traffic()

You can also add a search bar and use it to search for locations.

google_map(location = c(-37.81, 144.97), zoom = 8, search_box = T)

Markers and circles can both be used to represent points on the map. In this example the stops of tram route 35 are represented as both circles and markers.

google_map( data = tram_stops ) %>%
  add_circles() %>%
  add_markers()

This example also shows how you add multiple layers on the map by using the ‘pipe’ (%>%) operator.

And you can start to combine the services API with the mapping by quering Google’s directions service, and plotting the results on a map.

directions <- google_directions(
  origin = "Melbourne Airport, Australia"
  , destination = "Monash University, Melbourne"
)

df <- data.frame(polyline = direction_polyline(directions) )

google_map() %>%
  add_polylines( data = df, polyline = "polyline")

A choropleth is made by plotting coloured polygons on the map. In this example the polygons represent Statistical Areas (level 2) of melbourne, coloured according to the size of the region.

df <- melbourne
df$info <- paste0("SA2<br><b>",df$SA2_NAME,"</b>")

google_map() %>%
  add_polygons(
    data = df, fill_colour = "AREASQKM", stroke_colour = "AREASQKM", info_window = "info",
    palette = viridisLite::plasma
  )

---

Mapdeck

library(mapdeck)
set_token(read.dcf("~/Documents/.googleAPI", fields = "MAPBOX"))

The mapdeck library provides access to Uber’s Deck.gl framework, and uses Mapbox GL as the mapping layer. Deck.gl’s use of WebGL enables it to render large datasets (up to millions of points) quickly. It also provides a ‘2.5d’ perspective of data, where the user can tilt, drag and rotate the map (as well as pan and zoom), and view data ‘extruded’ to give a perspective of height. To use Mapbox (through mapdeck) you will need an access token

This choropleth is showing the same data as in the googelway choropleth example, but a random ‘elevation’ value is added to show the data extruded from the map. While elevation provides a nice visual effect, care has to be taken to ensure it is meaningful. … continue with height vs area vs mass vs data value…

df <- melbourne
df$elevation <- sample(100:5000, size = nrow(df))
df$info <- paste0("SA2<br><b>",df$SA2_NAME,"</b>")

mapdeck(style = mapdeck_style('dark') , location = c(145, -37.8) 
        ,pitch = 45, zoom = 10) %>%
  add_polygon(
    data = df, polyline = "geometry", layer = "polygon_layer", fill_colour = "AREASQKM",
    stroke_colour = "AREASQKM",elevation = "elevation", stroke_width = 0, tooltip = 'info',
    palette = viridisLite::plasma )

lines

mapdeck(
  style = 'mapbox://styles/mapbox/dark-v9'
  , location = c(145, -37.8)
  , zoom = 10) %>%
  add_path(
    data = roads
    , stroke_colour = "RIGHT_LOC"
    , layer_id = "path_layer"
    , tooltip = "ROAD_NAME"
    , auto_highlight = TRUE
  )

Shiny

All the interactive maps listed are built using the htmlwidgets framework. Which is natively supported inside Shiny applications. This means you can include the maps in an interactive dashboard.